• Proceedings of the Korea Database Society Conference
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• 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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• pp.361-371
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• 1999

This paper is concerned with designing and implementing the Internet shopping mall by using virtual reality-driven avatar and web decision support system. Traditionally, the Internet shopping mall has been designed based on the combination of several hyperlinks, images, and tents. However, this sort of approach results in a lower performance because possible customers cannot make more accurate shopping decisions. To overcome this kind of pitfalls facing the current Internet shopping malls, we propose using a combination of virtual reality and web DSS. The main virtues of our proposed approach to designing the Internet shopping mall are as follows: First, the virtual reality technique is emerging as one of alternatives guaranteeing a sense of reality for customers' part and facilitating the complex process of shopping decision makings. Especially, the avatar, which is an artificially designed man working on the Internet, can make easy and absorbing the Internet shopping-related decision making processes. Second, the web DSS approach can provide an effective decision support mechanism for customers. Especially, we design a set of intelligent agents for the proposed web DSS. Experimental results with an illustrative example showed that our proposed approach can yield a new Internet shopping mall paradigm with which customers can benefit from a high level of decision support functions.

• Information Systems Review
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• 제9권3호
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• pp.45-65
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• 2007

As digital economy era and knowledge society advent, division of the industry has been indistinctive and complex. This change of business environment has leaded todifficulty in operations of firms consisted of continuous decision making. To develop effective SDSS needs systematic strategic decision making process, efficient problem solving techniques, information of good quality, efficiently information system, and analysis ability of problem solver. This research develop SDSS framework combined strategic decision making process with various problem solving techniques for designing SDSS. Finally, this paper developed the technique recommendation system by selected the criterions of technique assortment.

• International Journal of Highway Engineering
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• 제16권4호
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• pp.127-134
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• 2014

PURPOSES : To operate more efficient traffic management system, it is utmost important to detect the change in congestion level on a freeway segment rapidly and reliably. This study aims to develop classification method of congestion change type. METHODS: This research proposes two classification methods to capture the change of the congestion level on freeway segments using the dedicated short range communication (DSRC) data and the vehicle detection system (VDS) data. For developing the classification methods, the decision tree models were employed in which the independent variable is the change in congestion level and the covariates are the DSRC and VDS data collected from the freeway segments in Korea. RESULTS : The comparison results show that the decision tree model with DSRC data are better than the decision tree model with VDS data. Specifically, the decision tree model using DSRC data with better fits show approximately 95% accuracies. CONCLUSIONS : It is expected that the congestion change type classified using the decision tree models could play an important role in future freeway traffic management strategy.

• 한국디지털정책학회:학술대회논문집
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• 한국디지털정책학회 2004년도 International Conference on Digital Policy & Management
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• pp.375-387
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• 2004

The paper presents an Integrated E-Community System (IECS) for management, decision and service, designed for the e-government project of Haishu District of Ningbo, Zhejiang, China. The project need is to promote the integration of management information and service information of communities, providing a unified platform on which different departments of the district government can share and exchange community information, government officers can analyze information and make decisions, and the outside users can access and request services. To meet the project need, the IECS consists of five parts: 1) The Central DataBase (CDB) that stores all information related with management, decision and service of communities: 2) Information Extracting Subsystem (IES) that provides functions of extracting data from data sources, transforming and loading them into the CDB for system administrators; 3) Information Management Subsystem (IMS) that provides functions of querying and sharing of information for government users, and functions of information maintenance, rights and log management for system administrators: 4) Intelligent Analysis Subsystem (IAS) that provides functions of extracting analysis related data from the CDB and loading them into the DW, and functions of multi-dimensional analysis and decision-making based on the DW and OLAP for government users; 5) Information Service Website (ISW) that provides functions of promulgating and collecting of information for government users and system administrators, and functions of browsing, querying and requesting of service information for outside users. The IECS supports management, decision and service of a government based on a unified data platform--the CDB, and ensures data security by providing different workplaces and rights for different users. In the real application, the system works well.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• 제23권1호
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• pp.38-46
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• 2012

In this paper, we propose a decision feedback equalizer based on LDPC(Low Density Parity Check) code for the fast processing and performance improvement in OFDM system. LDPC code has good error correcting capability and its performance approaches the Shannon capacity limit. However, it has longer parity check matrix and needs more iteration numbers. In our proposed system, MSE(Mean Square Error) of signal between decision device and decoder is fed back to equalizer. This proposed system can improve BER performance because it corrects estimated channel response more accurately. In addition, the proposed system can reduce complexity because it has a lower number of iterations than system without feedback at the same performance. Simulation results evaluate and show the performance of OFDM system with the CFO and phase noise in multipath channel.

• Information Systems Review
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• 제4권2호
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• pp.223-236
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• 2002

In an agent-based system, each agent has its own decision making capability and competes, cooperates, and communicates each other with an agent interface. Virtual manufacturing has characteristics as a typical application area of agent-based system: complex and time-bound decision making and negotiation. The time-boundness influences the choice of decision making models and design of protocols for internal and external negotiation. In this paper, we provide a case study which suggests a time-bound framework for external and internal negotiation between the agents for virtual manufacturing environment. We illustrate decision making model selection strategy and the system architecture of the agent-based system for the complex and time-bound environment.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• 제49권10호
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• pp.829-839
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• 2021

Autonomous system for UAVs has a capability to decide an appropriate current action to achieve the goal based on the ultimate mission goal, context of mission, and the current state of the UAV. We propose a decision-making system that has an ability to operate ISR mission autonomously under the realistic limitation such as low altitude operation with high risk of terrain collision, a set of way points without change of visit sequence not allowed, and position uncertainties of the objects for the mission. The proposed decision-making system is loaded to a Hardware-In-the-loop Simulation environment, then tested and verified using three representative scenarios with a realistic mission environment. The flight trajectories of the UAV and selected actions via the proposed decision-making system are presented as the simulation results with discussion.

• The Journal of the Korea Contents Association
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• 제21권12호
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• pp.13-22
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• 2021

The clinical decision support system uses accumulated medical data to apply an AI model learned by machine learning to patient diagnosis and treatment prediction. However, the existing black box-based AI application does not provide a valid reason for the result predicted by the system, so there is a limitation in that it lacks explanation. To compensate for these problems, this paper proposes a system model that applies XAI that can be explained in the development stage of the clinical decision support system. The proposed model can supplement the limitations of the black box by additionally applying a specific XAI technology that can be explained to the existing AI model. To show the application of the proposed model, we present an example of XAI application using LIME and SHAP. Through testing, it is possible to explain how data affects the prediction results of the model from various perspectives. The proposed model has the advantage of increasing the user's trust by presenting a specific reason to the user. In addition, it is expected that the active use of XAI will overcome the limitations of the existing clinical decision support system and enable better diagnosis and decision support.

• Proceedings of the Korea Water Resources Association Conference
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• 한국수자원학회 2005년도 학술발표회(1)
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• pp.66-67
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• 2005

• Proceedings of the Korea Society for Industrial Systems Conference
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• 한국산업정보학회 2003년도 추계공동학술대회
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• pp.239-250
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• 2003

In this research, we propose a hybrid group decision support mechanism (H-GDSM) based on Fuzzy AHP (Analytic Hierarchy Process) and FCM (Fuzzy Cognitive Map). The AHP elicits a corresponding priority vector interpreting the preferred information among the decision makers. Corresponding vector was composed of the pairwise comparison values of a set of objects. Since pairwise comparison values are the judgments obtained from an appropriate semantic scale. However, AHP couldn't represent the causal relationship among information, which were used by decision makers. In contrast to AHP, FCM could represent the causal relationship among variables or information. Therefore, FCMs were successfully developed and used in several ill-structured domains, such as strategic decision-making, policy making, and simulations. Nonetheless, many researchers used subjective and voluntary inputs to simulate the FCM. As a result of subjective inputs, it couldn't avoid the rebukes of businessman. To overcome these limitations, we incorporated the Fuzzy membership functions, AHP and FCM into a H-GDSM. In contrast to current AHP methods and FCMs, the H-GDSM method developed herein could concurrently tackle the pairwise comparison involving causal relationships under a group decision-making environment. The strengths and contributions of our mechanism were 1) handling of qualitative knowledge and causal relationships, 2) extraction of objective input value to simulate the FCM, 3) multi-phase group decision support based on H-GDSM. To validate our proposed mechanism we developed a simple prototype system to support negotiation-based decisions in electronic commerce (EC).